Ben Bolstad
| Snapshot Date: 2025-02-03 13:00 -0500 (Mon, 03 Feb 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-02-06 12:11 -0500 (Thu, 06 Feb 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4753 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4501 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4524 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4476 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4407 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.70.0 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz |
| StartedAt: 2025-02-04 05:14:49 -0000 (Tue, 04 Feb 2025) |
| EndedAt: 2025-02-04 05:15:12 -0000 (Tue, 04 Feb 2025) |
| EllapsedTime: 23.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz
###
##############################################################################
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* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 12.3.1 (openEuler 12.3.1-36.oe2403)
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.70.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-4.4.2/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -shared -L/home/biocbuild/R/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R/lib -lR
installing to /home/biocbuild/R/R-4.4.2/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.312 0.033 0.332
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 471793 25.2 1026264 54.9 643431 34.4
Vcells 871915 6.7 8388608 64.0 2046348 15.7
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Feb 4 05:15:06 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Feb 4 05:15:06 2025"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x2edc3c0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Feb 4 05:15:07 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Feb 4 05:15:07 2025"
>
> ColMode(tmp2)
<pointer: 0x2edc3c0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8102134 -1.5177410 -0.2704230 0.5432409
[2,] -1.6642256 0.3749382 1.1884474 -0.7807721
[3,] -0.5506818 1.2100640 1.2070617 -0.6524880
[4,] 1.3829472 -0.3079728 0.3449389 -0.1275230
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8102134 1.5177410 0.2704230 0.5432409
[2,] 1.6642256 0.3749382 1.1884474 0.7807721
[3,] 0.5506818 1.2100640 1.2070617 0.6524880
[4,] 1.3829472 0.3079728 0.3449389 0.1275230
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9905062 1.231966 0.5200221 0.7370488
[2,] 1.2900487 0.612322 1.0901593 0.8836131
[3,] 0.7420794 1.100029 1.0986636 0.8077673
[4,] 1.1759878 0.554953 0.5873150 0.3571036
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.71528 38.83740 30.47064 32.91373
[2,] 39.56471 31.49816 37.09004 34.61690
[3,] 32.97148 37.21035 37.19370 33.73016
[4,] 38.14282 30.85750 31.21809 28.69856
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x48c3ad0>
> exp(tmp5)
<pointer: 0x48c3ad0>
> log(tmp5,2)
<pointer: 0x48c3ad0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.7154
> Min(tmp5)
[1] 53.07201
> mean(tmp5)
[1] 72.84075
> Sum(tmp5)
[1] 14568.15
> Var(tmp5)
[1] 864.0795
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 86.99150 72.70176 73.42035 69.56115 71.47393 69.23931 71.98470 69.50058
[9] 71.03225 72.50200
> rowSums(tmp5)
[1] 1739.830 1454.035 1468.407 1391.223 1429.479 1384.786 1439.694 1390.012
[9] 1420.645 1450.040
> rowVars(tmp5)
[1] 8077.88917 87.79197 53.53173 60.52288 73.57332 82.75117
[7] 99.59383 96.48173 71.18961 92.59331
> rowSd(tmp5)
[1] 89.877078 9.369737 7.316538 7.779645 8.577489 9.096767 9.979671
[8] 9.822511 8.437393 9.622542
> rowMax(tmp5)
[1] 467.71540 90.50584 87.26269 89.08179 86.79000 84.05541 88.35687
[8] 84.96377 89.62238 89.85853
> rowMin(tmp5)
[1] 57.82959 57.85706 55.43645 56.86440 57.64852 54.80562 56.78394 53.07201
[9] 54.53339 54.45636
>
> colMeans(tmp5)
[1] 110.22048 69.12993 70.56346 70.65802 71.96384 69.57092 72.96599
[8] 75.35556 68.86389 67.37960 69.34343 71.35514 73.10808 70.32077
[15] 70.03871 68.12690 71.12197 71.51155 72.93976 72.27707
> colSums(tmp5)
[1] 1102.2048 691.2993 705.6346 706.5802 719.6384 695.7092 729.6599
[8] 753.5556 688.6389 673.7960 693.4343 713.5514 731.0808 703.2077
[15] 700.3871 681.2690 711.2197 715.1155 729.3976 722.7707
> colVars(tmp5)
[1] 15921.40995 74.06743 36.76147 59.24262 52.98864 51.68273
[7] 94.58767 83.98864 114.99336 60.85832 89.85030 75.82846
[13] 94.14979 151.49366 71.85724 31.06088 73.76039 121.58252
[19] 44.07662 89.97840
> colSd(tmp5)
[1] 126.180070 8.606243 6.063124 7.696923 7.279330 7.189070
[7] 9.725619 9.164532 10.723496 7.801174 9.478940 8.707954
[13] 9.703081 12.308276 8.476865 5.573229 8.588387 11.026446
[19] 6.639022 9.485694
> colMax(tmp5)
[1] 467.71540 80.83497 77.41381 79.91283 85.90398 76.60241 84.73967
[8] 87.90628 82.95733 78.28534 83.49908 83.92439 90.50584 89.85853
[15] 80.11186 78.03656 84.05541 87.26269 89.08179 88.35687
> colMin(tmp5)
[1] 56.70771 54.80562 59.92577 56.58192 64.75015 58.31077 60.27536 59.42000
[9] 54.45636 54.53339 53.07201 57.82959 58.40266 55.43645 57.40919 60.46629
[17] 56.86440 57.64852 64.65149 59.40366
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 86.99150 72.70176 73.42035 NA 71.47393 69.23931 71.98470 69.50058
[9] 71.03225 72.50200
> rowSums(tmp5)
[1] 1739.830 1454.035 1468.407 NA 1429.479 1384.786 1439.694 1390.012
[9] 1420.645 1450.040
> rowVars(tmp5)
[1] 8077.88917 87.79197 53.53173 63.46146 73.57332 82.75117
[7] 99.59383 96.48173 71.18961 92.59331
> rowSd(tmp5)
[1] 89.877078 9.369737 7.316538 7.966270 8.577489 9.096767 9.979671
[8] 9.822511 8.437393 9.622542
> rowMax(tmp5)
[1] 467.71540 90.50584 87.26269 NA 86.79000 84.05541 88.35687
[8] 84.96377 89.62238 89.85853
> rowMin(tmp5)
[1] 57.82959 57.85706 55.43645 NA 57.64852 54.80562 56.78394 53.07201
[9] 54.53339 54.45636
>
> colMeans(tmp5)
[1] 110.22048 69.12993 70.56346 70.65802 71.96384 69.57092 NA
[8] 75.35556 68.86389 67.37960 69.34343 71.35514 73.10808 70.32077
[15] 70.03871 68.12690 71.12197 71.51155 72.93976 72.27707
> colSums(tmp5)
[1] 1102.2048 691.2993 705.6346 706.5802 719.6384 695.7092 NA
[8] 753.5556 688.6389 673.7960 693.4343 713.5514 731.0808 703.2077
[15] 700.3871 681.2690 711.2197 715.1155 729.3976 722.7707
> colVars(tmp5)
[1] 15921.40995 74.06743 36.76147 59.24262 52.98864 51.68273
[7] NA 83.98864 114.99336 60.85832 89.85030 75.82846
[13] 94.14979 151.49366 71.85724 31.06088 73.76039 121.58252
[19] 44.07662 89.97840
> colSd(tmp5)
[1] 126.180070 8.606243 6.063124 7.696923 7.279330 7.189070
[7] NA 9.164532 10.723496 7.801174 9.478940 8.707954
[13] 9.703081 12.308276 8.476865 5.573229 8.588387 11.026446
[19] 6.639022 9.485694
> colMax(tmp5)
[1] 467.71540 80.83497 77.41381 79.91283 85.90398 76.60241 NA
[8] 87.90628 82.95733 78.28534 83.49908 83.92439 90.50584 89.85853
[15] 80.11186 78.03656 84.05541 87.26269 89.08179 88.35687
> colMin(tmp5)
[1] 56.70771 54.80562 59.92577 56.58192 64.75015 58.31077 NA 59.42000
[9] 54.45636 54.53339 53.07201 57.82959 58.40266 55.43645 57.40919 60.46629
[17] 56.86440 57.64852 64.65149 59.40366
>
> Max(tmp5,na.rm=TRUE)
[1] 467.7154
> Min(tmp5,na.rm=TRUE)
[1] 53.07201
> mean(tmp5,na.rm=TRUE)
[1] 72.87076
> Sum(tmp5,na.rm=TRUE)
[1] 14501.28
> Var(tmp5,na.rm=TRUE)
[1] 868.2625
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 86.99150 72.70176 73.42035 69.70284 71.47393 69.23931 71.98470 69.50058
[9] 71.03225 72.50200
> rowSums(tmp5,na.rm=TRUE)
[1] 1739.830 1454.035 1468.407 1324.354 1429.479 1384.786 1439.694 1390.012
[9] 1420.645 1450.040
> rowVars(tmp5,na.rm=TRUE)
[1] 8077.88917 87.79197 53.53173 63.46146 73.57332 82.75117
[7] 99.59383 96.48173 71.18961 92.59331
> rowSd(tmp5,na.rm=TRUE)
[1] 89.877078 9.369737 7.316538 7.966270 8.577489 9.096767 9.979671
[8] 9.822511 8.437393 9.622542
> rowMax(tmp5,na.rm=TRUE)
[1] 467.71540 90.50584 87.26269 89.08179 86.79000 84.05541 88.35687
[8] 84.96377 89.62238 89.85853
> rowMin(tmp5,na.rm=TRUE)
[1] 57.82959 57.85706 55.43645 56.86440 57.64852 54.80562 56.78394 53.07201
[9] 54.53339 54.45636
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.22048 69.12993 70.56346 70.65802 71.96384 69.57092 73.64342
[8] 75.35556 68.86389 67.37960 69.34343 71.35514 73.10808 70.32077
[15] 70.03871 68.12690 71.12197 71.51155 72.93976 72.27707
> colSums(tmp5,na.rm=TRUE)
[1] 1102.2048 691.2993 705.6346 706.5802 719.6384 695.7092 662.7908
[8] 753.5556 688.6389 673.7960 693.4343 713.5514 731.0808 703.2077
[15] 700.3871 681.2690 711.2197 715.1155 729.3976 722.7707
> colVars(tmp5,na.rm=TRUE)
[1] 15921.40995 74.06743 36.76147 59.24262 52.98864 51.68273
[7] 101.24837 83.98864 114.99336 60.85832 89.85030 75.82846
[13] 94.14979 151.49366 71.85724 31.06088 73.76039 121.58252
[19] 44.07662 89.97840
> colSd(tmp5,na.rm=TRUE)
[1] 126.180070 8.606243 6.063124 7.696923 7.279330 7.189070
[7] 10.062225 9.164532 10.723496 7.801174 9.478940 8.707954
[13] 9.703081 12.308276 8.476865 5.573229 8.588387 11.026446
[19] 6.639022 9.485694
> colMax(tmp5,na.rm=TRUE)
[1] 467.71540 80.83497 77.41381 79.91283 85.90398 76.60241 84.73967
[8] 87.90628 82.95733 78.28534 83.49908 83.92439 90.50584 89.85853
[15] 80.11186 78.03656 84.05541 87.26269 89.08179 88.35687
> colMin(tmp5,na.rm=TRUE)
[1] 56.70771 54.80562 59.92577 56.58192 64.75015 58.31077 60.27536 59.42000
[9] 54.45636 54.53339 53.07201 57.82959 58.40266 55.43645 57.40919 60.46629
[17] 56.86440 57.64852 64.65149 59.40366
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 86.99150 72.70176 73.42035 NaN 71.47393 69.23931 71.98470 69.50058
[9] 71.03225 72.50200
> rowSums(tmp5,na.rm=TRUE)
[1] 1739.830 1454.035 1468.407 0.000 1429.479 1384.786 1439.694 1390.012
[9] 1420.645 1450.040
> rowVars(tmp5,na.rm=TRUE)
[1] 8077.88917 87.79197 53.53173 NA 73.57332 82.75117
[7] 99.59383 96.48173 71.18961 92.59331
> rowSd(tmp5,na.rm=TRUE)
[1] 89.877078 9.369737 7.316538 NA 8.577489 9.096767 9.979671
[8] 9.822511 8.437393 9.622542
> rowMax(tmp5,na.rm=TRUE)
[1] 467.71540 90.50584 87.26269 NA 86.79000 84.05541 88.35687
[8] 84.96377 89.62238 89.85853
> rowMin(tmp5,na.rm=TRUE)
[1] 57.82959 57.85706 55.43645 NA 57.64852 54.80562 56.78394 53.07201
[9] 54.53339 54.45636
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.64616 69.67483 71.18425 71.87199 71.64567 70.08868 NaN
[8] 74.90766 68.68607 68.07440 69.71394 70.84341 73.32262 70.78530
[15] 70.54956 67.46955 72.70614 72.10338 71.14620 72.03983
> colSums(tmp5,na.rm=TRUE)
[1] 1022.8155 627.0735 640.6582 646.8479 644.8110 630.7981 0.0000
[8] 674.1690 618.1746 612.6696 627.4254 637.5907 659.9035 637.0677
[15] 634.9461 607.2259 654.3553 648.9304 640.3158 648.3585
> colVars(tmp5,na.rm=TRUE)
[1] 17779.56372 79.98557 37.02115 50.06857 58.47337 55.12715
[7] NA 92.23033 129.01179 63.03471 99.53721 82.36103
[13] 105.40071 168.00277 77.90349 30.08217 54.74734 132.83988
[19] 13.39660 100.59253
> colSd(tmp5,na.rm=TRUE)
[1] 133.340030 8.943465 6.084501 7.075914 7.646788 7.424766
[7] NA 9.603662 11.358336 7.939440 9.976834 9.075298
[13] 10.266485 12.961588 8.826296 5.484722 7.399145 11.525618
[19] 3.660136 10.029583
> colMax(tmp5,na.rm=TRUE)
[1] 467.71540 80.83497 77.41381 79.91283 85.90398 76.60241 -Inf
[8] 87.90628 82.95733 78.28534 83.49908 83.92439 90.50584 89.85853
[15] 80.11186 78.03656 84.05541 87.26269 75.83753 88.35687
> colMin(tmp5,na.rm=TRUE)
[1] 56.70771 54.80562 59.92577 56.58192 64.75015 58.31077 Inf 59.42000
[9] 54.45636 54.53339 53.07201 57.82959 58.40266 55.43645 57.40919 60.46629
[17] 61.01065 57.64852 64.65149 59.40366
>
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col <- 1
> cat(which.row," ",which.col,"\n")
3 1
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> rowVars(tmp5,na.rm=TRUE)
[1] 345.5974 320.4744 267.0759 145.7875 192.6162 221.6654 198.3897 271.5442
[9] 211.2812 255.0281
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 345.5974 320.4744 267.0759 145.7875 192.6162 221.6654 198.3897 271.5442
[9] 211.2812 255.0281
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 2.842171e-14 -5.684342e-14 -2.842171e-14 1.705303e-13 0.000000e+00
[6] -1.136868e-13 0.000000e+00 0.000000e+00 2.842171e-14 1.421085e-14
[11] 8.526513e-14 8.526513e-14 2.557954e-13 0.000000e+00 -2.842171e-14
[16] 1.705303e-13 8.526513e-14 8.526513e-14 5.684342e-14 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
3 19
6 13
7 13
6 12
1 1
5 2
8 1
4 3
4 13
8 9
3 18
10 3
2 8
5 17
6 18
3 8
6 6
2 4
1 12
7 20
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 1.958262
> Min(tmp)
[1] -2.974176
> mean(tmp)
[1] -0.07454819
> Sum(tmp)
[1] -7.454819
> Var(tmp)
[1] 0.8981142
>
> rowMeans(tmp)
[1] -0.07454819
> rowSums(tmp)
[1] -7.454819
> rowVars(tmp)
[1] 0.8981142
> rowSd(tmp)
[1] 0.9476889
> rowMax(tmp)
[1] 1.958262
> rowMin(tmp)
[1] -2.974176
>
> colMeans(tmp)
[1] 0.043308836 -0.693322398 -0.902715051 -1.333602805 0.830324159
[6] 1.360490291 0.383222446 -1.255205845 -0.081071354 0.850456132
[11] -1.046001426 0.017262182 0.707343524 -1.327973018 0.974527619
[16] 1.619095765 1.662691171 -0.709102595 0.448129444 -0.050973674
[21] -0.224304654 -0.290706199 1.958262316 0.540521496 -0.551084464
[26] -1.617234116 0.011220819 -1.793772042 1.143802361 -1.024760246
[31] 1.615743901 -0.060883363 -0.591007058 -0.398848941 0.659097655
[36] -1.011769016 -0.510933041 0.022407266 1.518823595 0.380113116
[41] -2.974175684 -1.988489060 0.452440668 -0.416828307 0.505917266
[46] -0.323373022 0.013090492 0.337604557 -1.140291979 0.374250350
[51] 0.156043826 -1.375795190 -0.360724314 -1.724320476 -0.192262509
[56] 0.050856226 0.559414109 -1.235159111 0.348922484 -1.312976278
[61] 1.580762182 -1.386603696 -0.575159393 -0.018867043 -0.282075857
[66] 0.751974946 -0.680165737 1.386134793 0.301345854 -0.998850180
[71] -0.374677260 -0.006331397 -0.722182863 1.388668597 0.292156789
[76] 0.153963431 0.506904090 1.641514649 0.343848140 0.292184427
[81] -0.398896135 0.192471589 0.050952517 0.237375480 -1.467022338
[86] -0.090246738 0.036760712 -0.708361939 -0.022506415 -0.747403809
[91] 1.072905342 0.128214273 -1.604912049 0.221001619 1.570118116
[96] -0.431430517 -0.996786555 0.867113030 -0.592369300 0.607942674
> colSums(tmp)
[1] 0.043308836 -0.693322398 -0.902715051 -1.333602805 0.830324159
[6] 1.360490291 0.383222446 -1.255205845 -0.081071354 0.850456132
[11] -1.046001426 0.017262182 0.707343524 -1.327973018 0.974527619
[16] 1.619095765 1.662691171 -0.709102595 0.448129444 -0.050973674
[21] -0.224304654 -0.290706199 1.958262316 0.540521496 -0.551084464
[26] -1.617234116 0.011220819 -1.793772042 1.143802361 -1.024760246
[31] 1.615743901 -0.060883363 -0.591007058 -0.398848941 0.659097655
[36] -1.011769016 -0.510933041 0.022407266 1.518823595 0.380113116
[41] -2.974175684 -1.988489060 0.452440668 -0.416828307 0.505917266
[46] -0.323373022 0.013090492 0.337604557 -1.140291979 0.374250350
[51] 0.156043826 -1.375795190 -0.360724314 -1.724320476 -0.192262509
[56] 0.050856226 0.559414109 -1.235159111 0.348922484 -1.312976278
[61] 1.580762182 -1.386603696 -0.575159393 -0.018867043 -0.282075857
[66] 0.751974946 -0.680165737 1.386134793 0.301345854 -0.998850180
[71] -0.374677260 -0.006331397 -0.722182863 1.388668597 0.292156789
[76] 0.153963431 0.506904090 1.641514649 0.343848140 0.292184427
[81] -0.398896135 0.192471589 0.050952517 0.237375480 -1.467022338
[86] -0.090246738 0.036760712 -0.708361939 -0.022506415 -0.747403809
[91] 1.072905342 0.128214273 -1.604912049 0.221001619 1.570118116
[96] -0.431430517 -0.996786555 0.867113030 -0.592369300 0.607942674
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.043308836 -0.693322398 -0.902715051 -1.333602805 0.830324159
[6] 1.360490291 0.383222446 -1.255205845 -0.081071354 0.850456132
[11] -1.046001426 0.017262182 0.707343524 -1.327973018 0.974527619
[16] 1.619095765 1.662691171 -0.709102595 0.448129444 -0.050973674
[21] -0.224304654 -0.290706199 1.958262316 0.540521496 -0.551084464
[26] -1.617234116 0.011220819 -1.793772042 1.143802361 -1.024760246
[31] 1.615743901 -0.060883363 -0.591007058 -0.398848941 0.659097655
[36] -1.011769016 -0.510933041 0.022407266 1.518823595 0.380113116
[41] -2.974175684 -1.988489060 0.452440668 -0.416828307 0.505917266
[46] -0.323373022 0.013090492 0.337604557 -1.140291979 0.374250350
[51] 0.156043826 -1.375795190 -0.360724314 -1.724320476 -0.192262509
[56] 0.050856226 0.559414109 -1.235159111 0.348922484 -1.312976278
[61] 1.580762182 -1.386603696 -0.575159393 -0.018867043 -0.282075857
[66] 0.751974946 -0.680165737 1.386134793 0.301345854 -0.998850180
[71] -0.374677260 -0.006331397 -0.722182863 1.388668597 0.292156789
[76] 0.153963431 0.506904090 1.641514649 0.343848140 0.292184427
[81] -0.398896135 0.192471589 0.050952517 0.237375480 -1.467022338
[86] -0.090246738 0.036760712 -0.708361939 -0.022506415 -0.747403809
[91] 1.072905342 0.128214273 -1.604912049 0.221001619 1.570118116
[96] -0.431430517 -0.996786555 0.867113030 -0.592369300 0.607942674
> colMin(tmp)
[1] 0.043308836 -0.693322398 -0.902715051 -1.333602805 0.830324159
[6] 1.360490291 0.383222446 -1.255205845 -0.081071354 0.850456132
[11] -1.046001426 0.017262182 0.707343524 -1.327973018 0.974527619
[16] 1.619095765 1.662691171 -0.709102595 0.448129444 -0.050973674
[21] -0.224304654 -0.290706199 1.958262316 0.540521496 -0.551084464
[26] -1.617234116 0.011220819 -1.793772042 1.143802361 -1.024760246
[31] 1.615743901 -0.060883363 -0.591007058 -0.398848941 0.659097655
[36] -1.011769016 -0.510933041 0.022407266 1.518823595 0.380113116
[41] -2.974175684 -1.988489060 0.452440668 -0.416828307 0.505917266
[46] -0.323373022 0.013090492 0.337604557 -1.140291979 0.374250350
[51] 0.156043826 -1.375795190 -0.360724314 -1.724320476 -0.192262509
[56] 0.050856226 0.559414109 -1.235159111 0.348922484 -1.312976278
[61] 1.580762182 -1.386603696 -0.575159393 -0.018867043 -0.282075857
[66] 0.751974946 -0.680165737 1.386134793 0.301345854 -0.998850180
[71] -0.374677260 -0.006331397 -0.722182863 1.388668597 0.292156789
[76] 0.153963431 0.506904090 1.641514649 0.343848140 0.292184427
[81] -0.398896135 0.192471589 0.050952517 0.237375480 -1.467022338
[86] -0.090246738 0.036760712 -0.708361939 -0.022506415 -0.747403809
[91] 1.072905342 0.128214273 -1.604912049 0.221001619 1.570118116
[96] -0.431430517 -0.996786555 0.867113030 -0.592369300 0.607942674
> colMedians(tmp)
[1] 0.043308836 -0.693322398 -0.902715051 -1.333602805 0.830324159
[6] 1.360490291 0.383222446 -1.255205845 -0.081071354 0.850456132
[11] -1.046001426 0.017262182 0.707343524 -1.327973018 0.974527619
[16] 1.619095765 1.662691171 -0.709102595 0.448129444 -0.050973674
[21] -0.224304654 -0.290706199 1.958262316 0.540521496 -0.551084464
[26] -1.617234116 0.011220819 -1.793772042 1.143802361 -1.024760246
[31] 1.615743901 -0.060883363 -0.591007058 -0.398848941 0.659097655
[36] -1.011769016 -0.510933041 0.022407266 1.518823595 0.380113116
[41] -2.974175684 -1.988489060 0.452440668 -0.416828307 0.505917266
[46] -0.323373022 0.013090492 0.337604557 -1.140291979 0.374250350
[51] 0.156043826 -1.375795190 -0.360724314 -1.724320476 -0.192262509
[56] 0.050856226 0.559414109 -1.235159111 0.348922484 -1.312976278
[61] 1.580762182 -1.386603696 -0.575159393 -0.018867043 -0.282075857
[66] 0.751974946 -0.680165737 1.386134793 0.301345854 -0.998850180
[71] -0.374677260 -0.006331397 -0.722182863 1.388668597 0.292156789
[76] 0.153963431 0.506904090 1.641514649 0.343848140 0.292184427
[81] -0.398896135 0.192471589 0.050952517 0.237375480 -1.467022338
[86] -0.090246738 0.036760712 -0.708361939 -0.022506415 -0.747403809
[91] 1.072905342 0.128214273 -1.604912049 0.221001619 1.570118116
[96] -0.431430517 -0.996786555 0.867113030 -0.592369300 0.607942674
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.04330884 -0.6933224 -0.9027151 -1.333603 0.8303242 1.36049 0.3832224
[2,] 0.04330884 -0.6933224 -0.9027151 -1.333603 0.8303242 1.36049 0.3832224
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.255206 -0.08107135 0.8504561 -1.046001 0.01726218 0.7073435 -1.327973
[2,] -1.255206 -0.08107135 0.8504561 -1.046001 0.01726218 0.7073435 -1.327973
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.9745276 1.619096 1.662691 -0.7091026 0.4481294 -0.05097367 -0.2243047
[2,] 0.9745276 1.619096 1.662691 -0.7091026 0.4481294 -0.05097367 -0.2243047
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.2907062 1.958262 0.5405215 -0.5510845 -1.617234 0.01122082 -1.793772
[2,] -0.2907062 1.958262 0.5405215 -0.5510845 -1.617234 0.01122082 -1.793772
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.143802 -1.02476 1.615744 -0.06088336 -0.5910071 -0.3988489 0.6590977
[2,] 1.143802 -1.02476 1.615744 -0.06088336 -0.5910071 -0.3988489 0.6590977
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.011769 -0.510933 0.02240727 1.518824 0.3801131 -2.974176 -1.988489
[2,] -1.011769 -0.510933 0.02240727 1.518824 0.3801131 -2.974176 -1.988489
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.4524407 -0.4168283 0.5059173 -0.323373 0.01309049 0.3376046 -1.140292
[2,] 0.4524407 -0.4168283 0.5059173 -0.323373 0.01309049 0.3376046 -1.140292
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3742503 0.1560438 -1.375795 -0.3607243 -1.72432 -0.1922625 0.05085623
[2,] 0.3742503 0.1560438 -1.375795 -0.3607243 -1.72432 -0.1922625 0.05085623
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.5594141 -1.235159 0.3489225 -1.312976 1.580762 -1.386604 -0.5751594
[2,] 0.5594141 -1.235159 0.3489225 -1.312976 1.580762 -1.386604 -0.5751594
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.01886704 -0.2820759 0.7519749 -0.6801657 1.386135 0.3013459 -0.9988502
[2,] -0.01886704 -0.2820759 0.7519749 -0.6801657 1.386135 0.3013459 -0.9988502
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.3746773 -0.006331397 -0.7221829 1.388669 0.2921568 0.1539634 0.5069041
[2,] -0.3746773 -0.006331397 -0.7221829 1.388669 0.2921568 0.1539634 0.5069041
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.641515 0.3438481 0.2921844 -0.3988961 0.1924716 0.05095252 0.2373755
[2,] 1.641515 0.3438481 0.2921844 -0.3988961 0.1924716 0.05095252 0.2373755
[,85] [,86] [,87] [,88] [,89] [,90]
[1,] -1.467022 -0.09024674 0.03676071 -0.7083619 -0.02250641 -0.7474038
[2,] -1.467022 -0.09024674 0.03676071 -0.7083619 -0.02250641 -0.7474038
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 1.072905 0.1282143 -1.604912 0.2210016 1.570118 -0.4314305 -0.9967866
[2,] 1.072905 0.1282143 -1.604912 0.2210016 1.570118 -0.4314305 -0.9967866
[,98] [,99] [,100]
[1,] 0.867113 -0.5923693 0.6079427
[2,] 0.867113 -0.5923693 0.6079427
>
>
> Max(tmp2)
[1] 2.340683
> Min(tmp2)
[1] -2.505556
> mean(tmp2)
[1] -0.1619875
> Sum(tmp2)
[1] -16.19875
> Var(tmp2)
[1] 0.9166773
>
> rowMeans(tmp2)
[1] -0.472216754 0.937508978 -1.070111779 0.983959710 -0.314806201
[6] 0.044854090 0.019703258 -0.008013715 -0.118763343 -0.030466135
[11] 1.395275753 -1.483955253 -0.399065622 1.004562730 0.062257686
[16] 1.138988308 0.263344192 0.316847929 -0.271919122 -0.744490754
[21] 0.017469906 -1.909356246 0.462879899 -0.228827662 -1.270446833
[26] -1.496454355 1.063192936 0.464142488 -1.549572052 -0.831094184
[31] -0.914224535 -0.331255875 -0.365718204 -0.435238344 -1.682057597
[36] -0.845361581 1.546244540 0.938066005 0.329122244 -0.402744999
[41] 0.191638405 -2.018634824 0.120197927 -0.821642569 -0.403723278
[46] -0.058673418 -0.056770559 -0.098458219 -0.822611036 1.166880272
[51] -2.505555569 -1.290949105 1.014917390 1.175712125 -0.098940910
[56] -1.177133852 -0.793343068 2.340683443 0.977740238 -0.028818723
[61] -0.794143723 1.984076746 0.142900375 -0.818726206 0.377746057
[66] 0.326798145 -0.199331830 2.069126812 -0.104885298 -1.336026349
[71] -0.361920544 -2.154760237 -0.525308208 -0.134245794 0.656255836
[76] -0.093856224 -0.039805066 -0.336958096 -0.654526012 -1.354977540
[81] -0.690162355 -0.963210970 0.198068291 1.034369861 0.152960194
[86] 0.716613599 -0.219286257 1.463838330 -1.150774157 -0.701028225
[91] -0.073138047 -1.739641223 -1.030442671 1.018818584 -1.511642148
[96] -1.031408900 0.053584118 0.976058852 -0.325419433 0.350883374
> rowSums(tmp2)
[1] -0.472216754 0.937508978 -1.070111779 0.983959710 -0.314806201
[6] 0.044854090 0.019703258 -0.008013715 -0.118763343 -0.030466135
[11] 1.395275753 -1.483955253 -0.399065622 1.004562730 0.062257686
[16] 1.138988308 0.263344192 0.316847929 -0.271919122 -0.744490754
[21] 0.017469906 -1.909356246 0.462879899 -0.228827662 -1.270446833
[26] -1.496454355 1.063192936 0.464142488 -1.549572052 -0.831094184
[31] -0.914224535 -0.331255875 -0.365718204 -0.435238344 -1.682057597
[36] -0.845361581 1.546244540 0.938066005 0.329122244 -0.402744999
[41] 0.191638405 -2.018634824 0.120197927 -0.821642569 -0.403723278
[46] -0.058673418 -0.056770559 -0.098458219 -0.822611036 1.166880272
[51] -2.505555569 -1.290949105 1.014917390 1.175712125 -0.098940910
[56] -1.177133852 -0.793343068 2.340683443 0.977740238 -0.028818723
[61] -0.794143723 1.984076746 0.142900375 -0.818726206 0.377746057
[66] 0.326798145 -0.199331830 2.069126812 -0.104885298 -1.336026349
[71] -0.361920544 -2.154760237 -0.525308208 -0.134245794 0.656255836
[76] -0.093856224 -0.039805066 -0.336958096 -0.654526012 -1.354977540
[81] -0.690162355 -0.963210970 0.198068291 1.034369861 0.152960194
[86] 0.716613599 -0.219286257 1.463838330 -1.150774157 -0.701028225
[91] -0.073138047 -1.739641223 -1.030442671 1.018818584 -1.511642148
[96] -1.031408900 0.053584118 0.976058852 -0.325419433 0.350883374
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -0.472216754 0.937508978 -1.070111779 0.983959710 -0.314806201
[6] 0.044854090 0.019703258 -0.008013715 -0.118763343 -0.030466135
[11] 1.395275753 -1.483955253 -0.399065622 1.004562730 0.062257686
[16] 1.138988308 0.263344192 0.316847929 -0.271919122 -0.744490754
[21] 0.017469906 -1.909356246 0.462879899 -0.228827662 -1.270446833
[26] -1.496454355 1.063192936 0.464142488 -1.549572052 -0.831094184
[31] -0.914224535 -0.331255875 -0.365718204 -0.435238344 -1.682057597
[36] -0.845361581 1.546244540 0.938066005 0.329122244 -0.402744999
[41] 0.191638405 -2.018634824 0.120197927 -0.821642569 -0.403723278
[46] -0.058673418 -0.056770559 -0.098458219 -0.822611036 1.166880272
[51] -2.505555569 -1.290949105 1.014917390 1.175712125 -0.098940910
[56] -1.177133852 -0.793343068 2.340683443 0.977740238 -0.028818723
[61] -0.794143723 1.984076746 0.142900375 -0.818726206 0.377746057
[66] 0.326798145 -0.199331830 2.069126812 -0.104885298 -1.336026349
[71] -0.361920544 -2.154760237 -0.525308208 -0.134245794 0.656255836
[76] -0.093856224 -0.039805066 -0.336958096 -0.654526012 -1.354977540
[81] -0.690162355 -0.963210970 0.198068291 1.034369861 0.152960194
[86] 0.716613599 -0.219286257 1.463838330 -1.150774157 -0.701028225
[91] -0.073138047 -1.739641223 -1.030442671 1.018818584 -1.511642148
[96] -1.031408900 0.053584118 0.976058852 -0.325419433 0.350883374
> rowMin(tmp2)
[1] -0.472216754 0.937508978 -1.070111779 0.983959710 -0.314806201
[6] 0.044854090 0.019703258 -0.008013715 -0.118763343 -0.030466135
[11] 1.395275753 -1.483955253 -0.399065622 1.004562730 0.062257686
[16] 1.138988308 0.263344192 0.316847929 -0.271919122 -0.744490754
[21] 0.017469906 -1.909356246 0.462879899 -0.228827662 -1.270446833
[26] -1.496454355 1.063192936 0.464142488 -1.549572052 -0.831094184
[31] -0.914224535 -0.331255875 -0.365718204 -0.435238344 -1.682057597
[36] -0.845361581 1.546244540 0.938066005 0.329122244 -0.402744999
[41] 0.191638405 -2.018634824 0.120197927 -0.821642569 -0.403723278
[46] -0.058673418 -0.056770559 -0.098458219 -0.822611036 1.166880272
[51] -2.505555569 -1.290949105 1.014917390 1.175712125 -0.098940910
[56] -1.177133852 -0.793343068 2.340683443 0.977740238 -0.028818723
[61] -0.794143723 1.984076746 0.142900375 -0.818726206 0.377746057
[66] 0.326798145 -0.199331830 2.069126812 -0.104885298 -1.336026349
[71] -0.361920544 -2.154760237 -0.525308208 -0.134245794 0.656255836
[76] -0.093856224 -0.039805066 -0.336958096 -0.654526012 -1.354977540
[81] -0.690162355 -0.963210970 0.198068291 1.034369861 0.152960194
[86] 0.716613599 -0.219286257 1.463838330 -1.150774157 -0.701028225
[91] -0.073138047 -1.739641223 -1.030442671 1.018818584 -1.511642148
[96] -1.031408900 0.053584118 0.976058852 -0.325419433 0.350883374
>
> colMeans(tmp2)
[1] -0.1619875
> colSums(tmp2)
[1] -16.19875
> colVars(tmp2)
[1] 0.9166773
> colSd(tmp2)
[1] 0.9574327
> colMax(tmp2)
[1] 2.340683
> colMin(tmp2)
[1] -2.505556
> colMedians(tmp2)
[1] -0.1118243
> colRanges(tmp2)
[,1]
[1,] -2.505556
[2,] 2.340683
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 5.0861554 -1.6064342 0.4194899 -0.3021636 -4.6319470 4.5368330
[7] -1.9913922 -8.3401776 -3.2698243 1.3002985
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.5325803
[2,] -0.1883647
[3,] 0.2143613
[4,] 1.1361450
[5,] 2.2979327
>
> rowApply(tmp,sum)
[1] 1.0669227 -1.9276706 0.3925547 2.6971664 1.5379465 -3.9487805
[7] -0.9792723 -1.6901194 -6.1972640 0.2493544
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 5 10 5 10 7 10 5 8 5
[2,] 4 4 6 3 3 9 8 3 7 4
[3,] 9 8 2 9 9 8 6 9 2 8
[4,] 1 6 4 10 8 2 3 6 10 3
[5,] 2 3 3 4 1 5 7 10 1 10
[6,] 10 1 9 8 4 4 9 8 6 9
[7,] 8 2 7 1 7 6 5 4 5 7
[8,] 3 10 5 2 5 1 1 1 3 1
[9,] 6 7 1 7 2 3 2 7 9 2
[10,] 5 9 8 6 6 10 4 2 4 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.0163878 -0.3167488 -4.0291422 -4.0755414 -2.6125650 -0.9089731
[7] -1.5488620 1.6161642 0.8888747 0.5803644 0.1558635 0.6610960
[13] -0.3868078 0.1541428 0.5867860 -2.1557888 -1.1769459 0.9987819
[19] -2.4405396 -3.9128568
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2103342
[2,] -0.6384104
[3,] -0.1122589
[4,] 0.4057603
[5,] 0.5388554
>
> rowApply(tmp,sum)
[1] -4.939143 -6.811784 -3.707623 4.061446 -7.541983
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 7 3 13 12
[2,] 9 1 19 12 14
[3,] 15 2 8 1 9
[4,] 4 10 10 4 3
[5,] 11 17 13 3 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.4057603 -0.4115175 0.1859135 -0.7193203 -0.2908943 -0.26363443
[2,] -0.6384104 -1.8752840 -1.5530855 -0.4166393 0.4251443 0.22531986
[3,] -1.2103342 1.2651169 -0.4865445 -0.4392686 0.1855078 -0.99865243
[4,] 0.5388554 0.5383258 -1.3842043 -0.8802999 -0.9176432 -0.02489483
[5,] -0.1122589 0.1666100 -0.7912214 -1.6200133 -2.0146797 0.15288872
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.45936210 -1.8819010 -0.4446520 1.6650688 0.18715413 -0.08601482
[2,] -0.43513607 0.1090159 -0.1797748 -0.8835220 0.06556599 -0.34219898
[3,] -0.23452894 1.7112672 1.0151044 0.1684775 -1.97747760 -0.83202767
[4,] -0.01350357 0.4044243 1.4670810 1.0797032 1.64350147 0.25840483
[5,] -0.40633130 1.2733579 -0.9688839 -1.4493632 0.23711954 1.66293265
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.4993944 0.8470944 -0.6721362 -0.3961012 -0.9918849 -0.01997357
[2,] 1.2760163 0.7470854 -0.7795537 -1.4926518 -1.0769183 0.47347924
[3,] -2.0165229 1.1911042 0.2929583 0.2017623 -1.2062240 0.75070625
[4,] 1.7064026 -0.4668047 0.7054418 0.6523077 0.9609930 -0.39136395
[5,] -0.8533095 -2.1643365 1.0400759 -1.1211058 1.1370883 0.18593395
[,19] [,20]
[1,] 0.5577633 -1.65111081
[2,] -0.5336074 0.07337148
[3,] -0.6288115 -0.45923505
[4,] -0.6671924 -1.14808780
[5,] -1.1686916 -0.72779458
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.2179285 0.5861326 -0.6417031 2.133818 1.466575 -0.2377997 -1.22659
col8 col9 col10 col11 col12 col13 col14
row1 -0.5677203 0.5416046 0.5658411 -0.5624129 -1.701492 1.798978 -1.961791
col15 col16 col17 col18 col19 col20
row1 -0.2131635 1.087938 0.07646379 0.04185231 -0.8775368 0.5181975
> tmp[,"col10"]
col10
row1 0.56584107
row2 -0.24410521
row3 0.66647218
row4 0.63309524
row5 0.04042793
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.2179285 0.5861326 -0.6417031 2.1338184 1.4665749 -0.2377997
row5 -2.3046938 -0.6095029 0.9049358 -0.4402905 -0.5836086 0.7900228
col7 col8 col9 col10 col11 col12
row1 -1.2265903 -0.5677203 0.5416046 0.56584107 -0.56241294 -1.701492
row5 0.1397363 1.1174351 0.1245346 0.04042793 0.09542079 1.052320
col13 col14 col15 col16 col17 col18
row1 1.79897835 -1.9617914 -0.2131635 1.087938 0.07646379 0.04185231
row5 0.03814043 0.5196647 1.4522751 1.530776 -1.15695032 -0.04187349
col19 col20
row1 -0.87753683 0.5181975
row5 -0.02280777 1.8302507
> tmp[,c("col6","col20")]
col6 col20
row1 -0.2377997 0.5181975
row2 -0.5138020 -0.3823035
row3 1.5465859 -0.9569891
row4 -2.7565371 0.2051704
row5 0.7900228 1.8302507
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.2377997 0.5181975
row5 0.7900228 1.8302507
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.77532 50.74227 49.97551 50.60433 50.30915 104.7828 51.86344 50.72222
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.09439 50.41448 49.90033 51.66297 50.28425 49.11459 50.89635 49.80487
col17 col18 col19 col20
row1 50.12236 50.91023 51.4609 104.6852
> tmp[,"col10"]
col10
row1 50.41448
row2 30.48516
row3 28.51502
row4 30.97215
row5 49.80248
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.77532 50.74227 49.97551 50.60433 50.30915 104.7828 51.86344 50.72222
row5 49.17492 49.90696 50.62489 49.81389 49.35850 105.2576 48.34963 50.42099
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.09439 50.41448 49.90033 51.66297 50.28425 49.11459 50.89635 49.80487
row5 49.14490 49.80248 50.63590 52.66029 49.26416 49.95834 48.68095 51.29928
col17 col18 col19 col20
row1 50.12236 50.91023 51.46090 104.6852
row5 50.64390 50.27806 48.93014 103.6253
> tmp[,c("col6","col20")]
col6 col20
row1 104.78281 104.68521
row2 76.02782 74.14971
row3 74.92907 75.64945
row4 76.41082 75.44593
row5 105.25758 103.62527
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7828 104.6852
row5 105.2576 103.6253
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7828 104.6852
row5 105.2576 103.6253
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.1458373
[2,] 0.1763394
[3,] 0.6109178
[4,] 0.2467420
[5,] -0.1744767
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.6094648 -0.08670102
[2,] -1.1926808 1.37786963
[3,] -0.8470168 2.17625774
[4,] 1.0866147 0.11168332
[5,] 2.0264852 -0.45934422
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.1732522 -2.2645268
[2,] 1.9589959 0.7331206
[3,] -1.2398062 -1.2982026
[4,] 1.0672631 0.1940705
[5,] 0.9237867 0.8923935
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.173252
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.173252
[2,] 1.958996
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -1.650581 -0.1884864 0.2783538 -0.1270167 -0.5936152 1.360676 0.7775746
row1 -1.818451 -0.6456398 1.2365653 0.1322991 -1.7483076 -1.541844 1.3972396
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.8477099 0.6191835 -0.9903833 0.842107 -0.9001047 -0.1642408 -0.7927246
row1 -0.5055393 0.1738448 0.1297537 1.273665 1.0461080 0.6560038 0.8903584
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.1951126 0.93943160 0.9417784 -0.6439113 -1.3895639 -0.3094732
row1 1.0106562 0.01962753 -0.8692332 0.2781718 0.3051989 -0.9761142
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.895691 0.1609186 1.117002 -0.4704831 -0.8170678 0.8701621 -0.4781998
[,8] [,9] [,10]
row2 0.5633394 -0.6495207 -0.417023
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.6321499 0.5640441 -0.04378241 0.5865931 0.3760933 1.713963 -0.2330407
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.077875 -1.033257 -0.763697 0.6737367 -1.28884 1.408491 0.4397947
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.2130539 -1.170033 1.227901 -0.5529803 0.3105059 0.9814877
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> colnames(tmp) <- NULL
> rownames(tmp) <- NULL
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> dimnames(tmp)
[[1]]
[1] "row1" "row2" "row3" "row4" "row5"
[[2]]
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
>
> dimnames(tmp) <- NULL
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> dimnames(tmp)
[[1]]
NULL
[[2]]
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
>
>
> dimnames(tmp) <- NULL
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> dimnames(tmp)
[[1]]
[1] "row1" "row2" "row3" "row4" "row5"
[[2]]
NULL
>
> dimnames(tmp) <- list(NULL,c(colnames(tmp,do.NULL=FALSE)))
> dimnames(tmp)
[[1]]
NULL
[[2]]
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
>
>
>
> ###
> ### Testing logical indexing
> ###
> ###
>
> tmp <- createBufferedMatrix(230,15)
> tmp[1:230,1:15] <- rnorm(230*15)
> x <-tmp[1:230,1:15]
>
> for (rep in 1:10){
+ which.cols <- sample(c(TRUE,FALSE),15,replace=T)
+ which.rows <- sample(c(TRUE,FALSE),230,replace=T)
+
+ if (!all(tmp[which.rows,which.cols] == x[which.rows,which.cols])){
+ stop("No agreement when logical indexing\n")
+ }
+
+ if (!all(subBufferedMatrix(tmp,,which.cols)[,1:sum(which.cols)] == x[,which.cols])){
+ stop("No agreement when logical indexing in subBufferedMatrix cols\n")
+ }
+ if (!all(subBufferedMatrix(tmp,which.rows,)[1:sum(which.rows),] == x[which.rows,])){
+ stop("No agreement when logical indexing in subBufferedMatrix rows\n")
+ }
+
+
+ if (!all(subBufferedMatrix(tmp,which.rows,which.cols)[1:sum(which.rows),1:sum(which.cols)]== x[which.rows,which.cols])){
+ stop("No agreement when logical indexing in subBufferedMatrix rows and columns\n")
+ }
+ }
>
>
> ##
> ## Test the ReadOnlyMode
> ##
>
> ReadOnlyMode(tmp)
<pointer: 0x481ffe0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM18444016ecc22b"
[2] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1844402778867a"
[3] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1844401d4d3ddc"
[4] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1844407ed08dff"
[5] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1844408457d77"
[6] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1844403cd7c867"
[7] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM184440693160d9"
[8] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM18444078eec4c7"
[9] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM18444050714117"
[10] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1844404f31ce96"
[11] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1844402fa320c1"
[12] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM184440eb435a8"
[13] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM184440398505ab"
[14] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM184440527da47e"
[15] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1844405ea4933f"
>
>
> ### testing coercion functions
> ###
>
> tmp <- as(tmp,"matrix")
> tmp <- as(tmp,"BufferedMatrix")
>
>
>
> ### testing whether can move storage from one location to another
>
> MoveStorageDirectory(tmp,"NewDirectory",full.path=FALSE)
<pointer: 0x48c9050>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x48c9050>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x48c9050>
> rowMedians(tmp)
[1] 0.016999825 0.463705456 -0.144095859 -0.030269853 -0.640771438
[6] -0.226524222 0.020546989 0.222732191 -0.355176300 -0.421198165
[11] -0.070735513 -0.262067015 0.465269878 0.233262038 0.132993008
[16] -0.223793506 0.051364511 0.001260708 -0.052574470 0.593205775
[21] 0.095520063 -0.157437555 -0.134403701 0.113876233 0.050447774
[26] 0.252362420 -0.301668284 -0.263528401 -0.015887134 0.261660085
[31] -0.080611376 0.353338338 -0.163044682 -0.082083169 1.049153303
[36] 0.272489317 0.011851163 0.003833875 -0.167839244 0.132951172
[41] 0.405047236 0.119304893 -0.014349987 0.301388975 0.828021282
[46] -0.340093980 -0.229611246 0.245798232 0.510886625 -0.012912505
[51] 0.321077103 -0.520285605 0.443373891 -0.931297782 0.012420799
[56] -0.041566146 0.012379523 0.196110050 -0.687018843 0.084728945
[61] -0.326635889 -0.636975385 0.629154631 -0.192547771 0.020168260
[66] 0.748340702 0.337224764 -0.265557023 0.258143368 -0.059736455
[71] -0.290613922 0.146069415 -0.338241988 -0.152667751 -0.290963469
[76] -0.210781794 -0.208989033 0.527564497 -0.221398435 0.274893924
[81] -0.052648598 -0.166611482 0.326197860 0.076712926 0.221744842
[86] 0.379730229 -0.079536535 -0.347764304 -0.474664449 0.495380215
[91] -0.020068948 -0.573262198 0.073802701 -0.012727068 0.390909833
[96] 0.138676805 -0.174935790 0.144548831 0.137996335 0.684715616
[101] 0.521467577 0.019217322 0.063208096 0.351204335 0.131721704
[106] -0.259042873 -0.136391158 0.212560448 -0.289520628 0.171794905
[111] -0.258353493 0.100239434 0.199591860 -0.175152387 -0.106120935
[116] 0.092912357 0.367709671 0.027400276 -0.003561458 0.142342041
[121] 0.236911356 0.095434605 -0.144893372 -0.231990923 -0.047845906
[126] -0.052579087 0.097519890 -0.520641154 0.529015775 0.667286966
[131] -0.061433442 -0.328127345 0.389121159 -0.236300600 0.234709104
[136] -0.352239737 -0.300378175 -0.348719637 -0.195227540 -0.367637150
[141] -0.072076135 0.333041952 -0.059281524 -0.219091270 -0.409388666
[146] -0.006468078 0.219974569 -0.158883089 -0.057922105 -0.594670620
[151] -0.388796036 -0.298643223 -0.004039964 -0.220418500 0.363090188
[156] 0.289017013 0.533258237 0.238535559 0.498174225 0.495730523
[161] 0.384671416 0.564039409 -0.163767004 0.297184301 0.491047824
[166] 0.521024082 -0.302525148 0.290601779 0.231505467 0.416447956
[171] -0.023804991 0.050470740 0.017371397 -0.599212821 0.038854904
[176] -0.471364143 0.324194456 0.657910217 -0.027707785 0.180007737
[181] -0.421448087 -0.100193481 0.610743167 -0.358584033 0.081593752
[186] -0.186642736 -0.016377003 -0.212057220 0.285417814 0.754914659
[191] 0.447125946 0.007341515 -0.130982190 0.006767842 -0.480075521
[196] -0.109223146 -0.174340774 0.046737855 0.851143210 -0.492485890
[201] 0.092454551 0.575047941 0.023964235 0.448441303 -0.268705374
[206] -0.555386260 0.609751217 0.019429544 -0.231249753 -0.427548760
[211] 0.331800929 -0.075204057 0.227123428 0.136034324 -0.198603533
[216] -0.428256880 0.109971658 0.081235337 -0.146909298 -0.535466361
[221] -0.172408871 -0.420435057 -0.709005938 -0.236174627 0.227479820
[226] -0.106954644 -0.238725448 -0.311731082 -0.643120891 -0.017737360
>
> proc.time()
user system elapsed
1.824 0.806 2.655
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x21f813c0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x21f813c0>
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 10
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x21f813c0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 10
Buffer Rows: 1
Buffer Cols: 1
Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000 0.000000 0.000000 0.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000 0.000000 0.000000 0.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000 0.000000 0.000000 0.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000 0.000000 0.000000 0.000000 0.000000
<pointer: 0x21f813c0>
> rm(P)
>
> #P <- .Call("R_bm_Destroy",P)
> #.Call("R_bm_Destroy",P)
> #.Call("R_bm_Test_C",P)
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,5)
[1] TRUE
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 0
Buffer Rows: 1
Buffer Cols: 1
Printing Values
<pointer: 0x21a63d60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x21a63d60>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 1
Buffer Rows: 1
Buffer Cols: 1
Printing Values
0.000000
0.000000
0.000000
0.000000
0.000000
<pointer: 0x21a63d60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x21a63d60>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 1
Buffer Cols: 1
Printing Values
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
<pointer: 0x21a63d60>
> rm(P)
>
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,5)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x220957e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x220957e0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 1
Buffer Cols: 1
Printing Values
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
<pointer: 0x220957e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x220957e0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5
Printing Values
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
<pointer: 0x220957e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x220957e0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5
Printing Values
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
<pointer: 0x220957e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x220957e0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5
Printing Values
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
0.000000 0.000000
<pointer: 0x220957e0>
> rm(P)
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x2298afd0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x2298afd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2298afd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2298afd0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1845da4b3e946" "BufferedMatrixFile1845da708f2829"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1845da4b3e946" "BufferedMatrixFile1845da708f2829"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x22207da0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x22207da0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x22207da0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x22207da0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x22207da0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x22207da0>
> .Call("R_bm_isRowMode",P)
[1] FALSE
> rm(P)
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x24276990>
> .Call("R_bm_AddColumn",P)
<pointer: 0x24276990>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x24276990>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x24276990>
> rm(P)
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x242c3cc0>
> .Call("R_bm_getValue",P,3,3)
[1] 6
>
> .Call("R_bm_getValue",P,100000,10000)
[1] NA
> .Call("R_bm_setValue",P,3,3,12345.0)
[1] TRUE
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 12345.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x242c3cc0>
> rm(P)
>
> proc.time()
user system elapsed
0.343 0.029 0.357
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.319 0.026 0.330